generate_image

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral burden and discloses useful traits: output format (high-res WebP), AI quality review, supported aspect ratios, and accepted photography modifiers. It leaves some ambiguity about how the generated image is returned or what happens if quality review fails, but covers the core behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-organized into overview, prompt structure/example, and modifiers, with no filler. It front-loads the purpose and output constraints, and every section adds practical value for invocation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 2-parameter tool with 100% schema coverage and no output schema, the description is largely complete: it covers prompt construction, modifiers, aspect ratios, and output format. It does not fully explain return mechanics or explicitly distinguish when to prefer specialized sibling generators, so it is not a 5.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description goes beyond the schema by defining a prompt structure and listing camera angles, lighting, focus, lens, and quality-enhancer options. This gives the agent practical guidance for constructing the description parameter, while aspect_ratio is already fully documented in the enum.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: 'Generate photorealistic product images from text descriptions using Imagen AI.' It also names concrete capabilities (5 aspect ratios, high-res WebP output) that set it apart from sibling edit/crop/clean tools and from specialized jewelry generators.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The opening sentence provides a clear use case: create a new photorealistic product image from text. The prompt-structure guidance further clarifies how to use it. It does not explicitly name sibling alternatives or when-not-to-use cases, so it stops short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.